Displaying all 3 publications

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  1. Arebey M, Hannan MA, Basri H, Begum RA, Abdullah H
    Environ Monit Assess, 2011 Jun;177(1-4):399-408.
    PMID: 20703798 DOI: 10.1007/s10661-010-1642-x
    The integration of communication technologies such as radio frequency identification (RFID), global positioning system (GPS), general packet radio system (GPRS), and geographic information system (GIS) with a camera are constructed for solid waste monitoring system. The aim is to improve the way of responding to customer's inquiry and emergency cases and estimate the solid waste amount without any involvement of the truck driver. The proposed system consists of RFID tag mounted on the bin, RFID reader as in truck, GPRS/GSM as web server, and GIS as map server, database server, and control server. The tracking devices mounted in the trucks collect location information in real time via the GPS. This information is transferred continuously through GPRS to a central database. The users are able to view the current location of each truck in the collection stage via a web-based application and thereby manage the fleet. The trucks positions and trash bin information are displayed on a digital map, which is made available by a map server. Thus, the solid waste of the bin and the truck are being monitored using the developed system.
    Matched MeSH terms: Refuse Disposal/statistics & numerical data
  2. Fauziah SH, Agamuthu P
    Waste Manag Res, 2012 Jul;30(7):656-63.
    PMID: 22455994 DOI: 10.1177/0734242X12437564
    In Malaysia, landfills are being filled up rapidly due to the current daily generation of approximately 30,000 tonnes of municipal solid waste. This situation creates the crucial need for improved landfilling practices, as sustainable landfilling technology is yet to be achieved here. The objective of this paper is to identify and evaluate the development and trends in landfilling practices in Malaysia. In 1970, the disposal sites in Malaysia were small and prevailing waste disposal practices was mere open-dumping. This network of relatively small dumps, typically located close to population centres, was considered acceptable for a relatively low population of 10 million in Malaysia. In the 1980s, a national programme was developed to manage municipal and industrial wastes more systematically and to reduce adverse environmental impacts. The early 1990s saw the privatization of waste management in many parts of Malaysia, and the establishment of the first sanitary landfills for MSW and an engineered landfill (called 'secure landfill' in Malaysia) for hazardous waste. A public uproar in 2007 due to contamination of a drinking water source from improper landfilling practices led to some significant changes in the government's policy regarding the country's waste management strategy. Parliament passed the Solid Waste and Public Cleansing Management (SWPCM) Act 2007 in August 2007. Even though the Act is yet to be implemented, the government has taken big steps to improve waste management system further. The future of the waste management in Malaysia seems somewhat brighter with a clear waste management policy in place. There is now a foundation upon which to build a sound and sustainble waste management and disposal system in Malaysia.
    Matched MeSH terms: Refuse Disposal/statistics & numerical data
  3. Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, Younes MY
    Waste Manag, 2016 Sep;55:3-11.
    PMID: 26522806 DOI: 10.1016/j.wasman.2015.10.020
    Solid waste prediction is crucial for sustainable solid waste management. The collection of accurate waste data records is challenging in developing countries. Solid waste generation is usually correlated with economic, demographic and social factors. However, these factors are not constant due to population and economic growth. The objective of this research is to minimize the land requirements for solid waste disposal for implementation of the Malaysian vision of waste disposal options. This goal has been previously achieved by integrating the solid waste forecasting model, waste composition and the Malaysian vision. The modified adaptive neural fuzzy inference system (MANFIS) was employed to develop a solid waste prediction model and search for the optimum input factors. The performance of the model was evaluated using the root mean square error (RMSE) and the coefficient of determination (R(2)). The model validation results are as follows: RMSE for training=0.2678, RMSE for testing=3.9860 and R(2)=0.99. Implementation of the Malaysian vision for waste disposal options can minimize the land requirements for waste disposal by up to 43%.
    Matched MeSH terms: Refuse Disposal/statistics & numerical data
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